Protein conformational transitions are fundamental to signaling, enzyme catalysis, and assembly of cellular structures. Developing a quantitative understanding of how proteins interconvert between different folded structures is a grand challenge in biology; meeting this challenge would have an impact in treating a large number of diseases that are linked to signaling cascades or enzymes. This proposal aims to understand the physical principles that control protein conformational transitions by characterizing transitio pathways in proteins. Since these pathways are very complex, homologous proteins will be compared to make this aim feasible. We focus on a signaling proteins from the two-component system family (NtrC) and homologs of the enzyme adenylate kinase (Adk) from E. coli and extremophiles. These Adk homologs have optimal enzymatic activity at extreme temperature or pressure. An iterative approach between NMR dynamics experiments, advanced computational methods and functional assays is proposed. (1) Structures of stable conformational states and rates of interconversion between them are measured experimentally, (2) transition pathways are computationally characterized in atomistic detail, (3) crucial interactions that facilitate pathway are identified, (4) mutations are designed that disable these interactions, (5) the resulting changes in interconversion rates are measured experimentally, and (6) new computations are performed based on experimental observations. By comparing transition pathways among homologous proteins and mutants key residues are identified that lead to mechanistic differences, and confer their respective temperature or pressure behaviors. Furthermore, determining interconversion entropy and entropy changes for these enzymes adapted to extreme environments may shed light on the evolutionary selection mechanisms that shaped primitive enzymes. In a broader context, knowledge gained from the molecular pathways may elucidate general principles of conformational transitions in proteins, thereby expanding our understanding of protein energy landscapes from the ground states to transition landscapes.